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# Prometheus Wrapper
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The `prometheus` wrapper package exposes standard request metrics (request
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count, latency, errors) for go-micro services and clients, so they can be
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scraped by a Prometheus server with zero extra boilerplate.
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Resolves [micro/go-micro#2893](https://github.com/micro/go-micro/issues/2893).
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## Installation
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```go
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import prom "go-micro.dev/v5/wrapper/monitoring/prometheus"
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```
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## Exported Metrics
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All metrics are labelled with `service`, `endpoint` and `status`
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(`"success"` or `"fail"`). Labels are kept small on purpose to avoid
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blowing up Prometheus memory.
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| Metric | Type | Description |
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|---------------------------------|-----------|---------------------------------------------|
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| `micro_request_total` | Counter | Total number of requests handled. |
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| `micro_request_duration_seconds`| Histogram | Request latency distribution (seconds). |
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The `micro` prefix can be overridden with `prom.ServiceName("myapp")`.
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## Basic Usage
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```go
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import (
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"go-micro.dev/v5"
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prom "go-micro.dev/v5/wrapper/monitoring/prometheus"
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)
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func main() {
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service := micro.NewService(
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micro.Name("example.service"),
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micro.WrapHandler(prom.NewHandlerWrapper()),
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micro.WrapClient(prom.NewClientWrapper()),
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micro.WrapSubscriber(prom.NewSubscriberWrapper()),
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)
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service.Init()
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if err := service.Run(); err != nil {
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panic(err)
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}
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}
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```
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To expose the metrics to Prometheus, serve the default `promhttp` handler
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on a side HTTP endpoint:
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```go
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import (
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"net/http"
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"github.com/prometheus/client_golang/prometheus/promhttp"
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)
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go func() {
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http.Handle("/metrics", promhttp.Handler())
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_ = http.ListenAndServe(":9100", nil)
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}()
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```
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Then point Prometheus at it:
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```yaml
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scrape_configs:
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- job_name: 'example.service'
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static_configs:
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- targets: ['localhost:9100']
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```
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## Wrappers
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| Constructor | Wraps | Notes |
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|---------------------------|-------------------------|--------------------------------------------|
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| `NewHandlerWrapper` | `server.HandlerWrapper` | Incoming RPC handlers. |
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| `NewSubscriberWrapper` | `server.SubscriberWrapper` | Event subscribers (uses topic as endpoint). |
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| `NewCallWrapper` | `client.CallWrapper` | Outgoing unary RPC calls only. |
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| `NewClientWrapper` | `client.Wrapper` | Outgoing `Call` **and** `Publish`. |
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`NewClientWrapper` is the right choice when you want metrics for both
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`Call` and `Publish`; use `NewCallWrapper` if you only care about unary
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calls and want lower overhead.
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## Configuration
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All constructors accept functional options:
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```go
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prom.NewHandlerWrapper(
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prom.ServiceName("myapp"), // metric name prefix
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prom.Namespace("prod"), // Prometheus namespace
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prom.Subsystem("api"), // Prometheus subsystem
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prom.ConstLabels(prometheus.Labels{"dc": "eu-1"}), // labels on every metric
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prom.Buckets([]float64{0.005, 0.05, 0.5, 1, 5}), // latency buckets
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prom.Registerer(myRegistry), // custom registerer
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)
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```
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Defaults:
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- `ServiceName`: `"micro"`
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- `Buckets`: `prometheus.DefBuckets`
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- `Registerer`: `prometheus.DefaultRegisterer`
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## Reusing Collectors
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Creating multiple wrappers with the same options (e.g. `NewHandlerWrapper`
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and `NewClientWrapper` together) is safe: the collectors are cached per
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`(name, namespace, subsystem)` triple and `AlreadyRegisteredError` from
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Prometheus is handled transparently, so the existing collector is reused.
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## Testing
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The package ships with unit tests that use a fresh `prometheus.Registry`
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per test to keep assertions isolated:
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```bash
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go test ./wrapper/monitoring/prometheus/...
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```
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## License
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Apache 2.0
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